Agents

An analyst that shows every step

Give an agent a goal or a playbook. It works breadth first, then depth, calling the same tools you use, and concludes with findings that point at their evidence.

The run

The trace on the left, the conclusion on the right

Each step is recorded the moment it happens and streamed to the page: the tool, its arguments, a one-line summary of the result, the milliseconds and whether it succeeded. The answer has a headline, up to six findings with links into the console, the charts and session lists from the steps it chose to show, and follow-up questions.

  • Breadth first: overview and period comparison, then drivers
  • Depth next: journeys, zones, forms or errors, whichever the evidence points to
  • Proof last: sessions to watch, or an investigation over many of them
  • At most 12 tool calls by default (20 at most) and a 150-second budget; an identical call is refused with a pointer to the earlier step
clickiq.example.com/agents/runs
AI agent run titled ‘Orders fell -32.7% in 7d — a JS crash introduced in v2.4 (Oct 20) is blocking checkout…’ with a 10-step trace on the left (web_overview, compare_periods, run_query, drivers, journey_dropoff, errors, error_detail, list_annotations) and the answer plus findings cards on the right.
Every tool call is listed with its result and timing, for example ‘journey_dropoff: 218 did the step, 107 dropped (49%)’. The answer names the cause, ‘Uncaught TypeError: Cannot read properties of undefined (reading ‘days’) — app.js:217’, fired 309 times for 80 users, and ranks the fixes: hotfix app.js:217 first, then the ‘Apply coupon’ button.
Playbooks

Nine playbooks, each schedulable daily or weekly

A signal’s “Analyze with an agent” picks the right one: frustration goes to the Frustration hunter, an error spike to Error triage, a conversion drop to the Conversion analyst, a slow page to Page audit.

PlaybookWhat it looks at
Conversion analystConversion against the previous period, drivers, the funnel and the sessions that dropped
Frustration hunterRage and dead clicks, the zones that cause them and the sessions behind them
Traffic analystSources, campaigns, countries and devices that moved, and whether conversion moved with them
Page auditOne page: its zones, scroll reach, vitals and errors
Journey explorerPatterns, golden paths, loops and the biggest drop-off
Error triageThe top error (or a given fingerprint): trend, pages, browsers, sessions affected
Form doctorThe worst form: drop-off field, slow fields, refills, errors
Weekly reviewThe week across traffic, conversion, signals and quality (scheduled weekly by default)
Install healthIs the snippet sending what it should: custom events, identify, vitals, forms, replay coverage (daily by default)
How it works

The agent loop: plan a call, run it through the registry, record the step, repeat, then finish with evidence

The agent loop: plan a call, run it through the registry, record the step, repeat, then finish with evidence 1Goal or playbookFree text, a playbookwith its context, asignal, or Ask withDeep analysis on.2AIModel picks atoolFrom the sharedregistry: queries,drivers, journeys,zones, forms, errors,sessions.3Registry runs itRequired keyschecked, unknown onesdropped,tenant-pinned,results compacted.4Step recordedTool, arguments,summary,milliseconds, status;streamed to the pagelive.5FinishHeadline, answer,findings with consolelinks, and the stepsshown as evidence.Model unavailable: the playbook's deterministic plan runs the same tools and a rules writer words the answer (mode: rules).The agent loop: plan a call, run it through the registry, record the step, repeat, then finish with evidence 1Goal or playbookFree text, a playbook with itscontext, a signal, or Ask withDeep analysis on.2AIModel picks a toolFrom the shared registry: queries,drivers, journeys, zones, forms,errors, sessions.3Registry runs itRequired keys checked, unknownones dropped, tenant-pinned,results compacted.4Step recordedTool, arguments, summary,milliseconds, status; streamed tothe page live.5FinishHeadline, answer, findings withconsole links, and the steps shownas evidence.Model unavailable: the playbook'sdeterministic plan runs the same toolsand a rules writer words the answer(mode: rules).
Write tools (create a dashboard, segment, annotation or alert; start an investigation) need an editor role, for agents and for MCP callers alike.
What you can ask

Questions this answers

Type them into Ask, give them to an agent as a goal, or send them through MCP from your own assistant.

Why did checkout conversion fall after the v2.4 release?Conversion analyst: drivers, funnel, errors, sessions
Which element frustrates people most this week?Frustration hunter: the rage and dead zones with sessions
Audit /products/NW-JKT-001Page audit: zones, scroll, vitals and errors for one page
What is the most common path to a purchase?Journey explorer: golden path and the biggest drop
Is our tracking healthy?Install health: what is missing, as tips
Review the weekWeekly review, delivered on a schedule
Outcomes

What teams do with it

A second analyst on call

Playbooks run daily or weekly on a schedule and leave a finished run to read.

Reasoning you can audit

Every claim traces to a step; every step shows its arguments and result.

Action from the finding

Findings link to the console screen, or create the dashboard, segment or alert for an editor.

Where it stops. An agent is bounded by its tools and its budget: it reads your analytics, not your code or your CRM. It concludes from what the tools returned; if a question needs data that was never captured, the answer says what is missing.

Run a playbook on your data

We schedule the Weekly review on your project and read the first run together.

Request a demo